================================================================================================================
## [1] 4898 18
## [1] 1599 18
White wine overview
## [1] "X" "fixed.acidity" "volatile.acidity"
## [4] "citric.acid" "residual.sugar" "chlorides"
## [7] "free.sulfur.dioxide" "total.sulfur.dioxide" "density"
## [10] "pH" "sulphates" "alcohol"
## [13] "quality" "type" "combined.acidity"
## [16] "s.a.ratio" "taste" "taste.due.to.pH"
## 'data.frame': 4898 obs. of 18 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ fixed.acidity : num 7 6.3 8.1 7.2 7.2 8.1 6.2 7 6.3 8.1 ...
## $ volatile.acidity : num 0.27 0.3 0.28 0.23 0.23 0.28 0.32 0.27 0.3 0.22 ...
## $ citric.acid : num 0.36 0.34 0.4 0.32 0.32 0.4 0.16 0.36 0.34 0.43 ...
## $ residual.sugar : num 20.7 1.6 6.9 8.5 8.5 6.9 7 20.7 1.6 1.5 ...
## $ chlorides : num 0.045 0.049 0.05 0.058 0.058 0.05 0.045 0.045 0.049 0.044 ...
## $ free.sulfur.dioxide : num 45 14 30 47 47 30 30 45 14 28 ...
## $ total.sulfur.dioxide: num 170 132 97 186 186 97 136 170 132 129 ...
## $ density : num 1.001 0.994 0.995 0.996 0.996 ...
## $ pH : num 3 3.3 3.26 3.19 3.19 3.26 3.18 3 3.3 3.22 ...
## $ sulphates : num 0.45 0.49 0.44 0.4 0.4 0.44 0.47 0.45 0.49 0.45 ...
## $ alcohol : num 8.8 9.5 10.1 9.9 9.9 10.1 9.6 8.8 9.5 11 ...
## $ quality : int 6 6 6 6 6 6 6 6 6 6 ...
## $ type : Ord.factor w/ 1 level "White": 1 1 1 1 1 1 1 1 1 1 ...
## $ combined.acidity : num 7.63 6.94 8.78 7.75 7.75 8.78 6.68 7.63 6.94 8.75 ...
## $ s.a.ratio : num 2.713 0.231 0.786 1.097 1.097 ...
## $ taste : Ord.factor w/ 4 levels "Dry"<"Medium_Dry"<..: 3 1 1 2 2 1 2 3 1 1 ...
## $ taste.due.to.pH : Ord.factor w/ 4 levels "Dry"<"Medium_Dry"<..: 3 2 1 2 2 1 2 3 2 1 ...
Red wine overview
## [1] "X" "fixed.acidity" "volatile.acidity"
## [4] "citric.acid" "residual.sugar" "chlorides"
## [7] "free.sulfur.dioxide" "total.sulfur.dioxide" "density"
## [10] "pH" "sulphates" "alcohol"
## [13] "quality" "type" "combined.acidity"
## [16] "s.a.ratio" "taste" "taste.due.to.pH"
## 'data.frame': 1599 obs. of 18 variables:
## $ X : int 1 2 3 4 5 6 7 8 9 10 ...
## $ fixed.acidity : num 7.4 7.8 7.8 11.2 7.4 7.4 7.9 7.3 7.8 7.5 ...
## $ volatile.acidity : num 0.7 0.88 0.76 0.28 0.7 0.66 0.6 0.65 0.58 0.5 ...
## $ citric.acid : num 0 0 0.04 0.56 0 0 0.06 0 0.02 0.36 ...
## $ residual.sugar : num 1.9 2.6 2.3 1.9 1.9 1.8 1.6 1.2 2 6.1 ...
## $ chlorides : num 0.076 0.098 0.092 0.075 0.076 0.075 0.069 0.065 0.073 0.071 ...
## $ free.sulfur.dioxide : num 11 25 15 17 11 13 15 15 9 17 ...
## $ total.sulfur.dioxide: num 34 67 54 60 34 40 59 21 18 102 ...
## $ density : num 0.998 0.997 0.997 0.998 0.998 ...
## $ pH : num 3.51 3.2 3.26 3.16 3.51 3.51 3.3 3.39 3.36 3.35 ...
## $ sulphates : num 0.56 0.68 0.65 0.58 0.56 0.56 0.46 0.47 0.57 0.8 ...
## $ alcohol : num 9.4 9.8 9.8 9.8 9.4 9.4 9.4 10 9.5 10.5 ...
## $ quality : int 5 5 5 6 5 5 5 7 7 5 ...
## $ type : Ord.factor w/ 1 level "Red": 1 1 1 1 1 1 1 1 1 1 ...
## $ combined.acidity : num 8.1 8.68 8.6 12.04 8.1 ...
## $ s.a.ratio : num 0.235 0.3 0.267 0.158 0.235 ...
## $ taste : Ord.factor w/ 2 levels "Dry"<"Medium_Dry": 1 1 1 1 1 1 1 1 1 1 ...
## $ taste.due.to.pH : Ord.factor w/ 3 levels "Dry"<"Medium_Dry"<..: 3 1 1 1 3 3 2 2 2 2 ...
## [1] 6497 18
## [1] 3 4 5 6 7 8 9
White Wine
## X fixed.acidity volatile.acidity citric.acid
## Min. : 1 Min. : 3.800 Min. :0.0800 Min. :0.0000
## 1st Qu.:1225 1st Qu.: 6.300 1st Qu.:0.2100 1st Qu.:0.2700
## Median :2450 Median : 6.800 Median :0.2600 Median :0.3200
## Mean :2450 Mean : 6.855 Mean :0.2782 Mean :0.3342
## 3rd Qu.:3674 3rd Qu.: 7.300 3rd Qu.:0.3200 3rd Qu.:0.3900
## Max. :4898 Max. :14.200 Max. :1.1000 Max. :1.6600
## residual.sugar chlorides free.sulfur.dioxide
## Min. : 0.600 Min. :0.00900 Min. : 2.00
## 1st Qu.: 1.700 1st Qu.:0.03600 1st Qu.: 23.00
## Median : 5.200 Median :0.04300 Median : 34.00
## Mean : 6.391 Mean :0.04577 Mean : 35.31
## 3rd Qu.: 9.900 3rd Qu.:0.05000 3rd Qu.: 46.00
## Max. :65.800 Max. :0.34600 Max. :289.00
## total.sulfur.dioxide density pH sulphates
## Min. : 9.0 Min. :0.9871 Min. :2.720 Min. :0.2200
## 1st Qu.:108.0 1st Qu.:0.9917 1st Qu.:3.090 1st Qu.:0.4100
## Median :134.0 Median :0.9937 Median :3.180 Median :0.4700
## Mean :138.4 Mean :0.9940 Mean :3.188 Mean :0.4898
## 3rd Qu.:167.0 3rd Qu.:0.9961 3rd Qu.:3.280 3rd Qu.:0.5500
## Max. :440.0 Max. :1.0390 Max. :3.820 Max. :1.0800
## alcohol quality type combined.acidity
## Min. : 8.00 Min. :3.000 White:4898 Min. : 4.130
## 1st Qu.: 9.50 1st Qu.:5.000 1st Qu.: 6.890
## Median :10.40 Median :6.000 Median : 7.405
## Mean :10.51 Mean :5.878 Mean : 7.467
## 3rd Qu.:11.40 3rd Qu.:6.000 3rd Qu.: 7.960
## Max. :14.20 Max. :9.000 Max. :14.960
## s.a.ratio taste taste.due.to.pH
## Min. :0.06459 Dry :3053 Dry :2286
## 1st Qu.:0.23495 Medium_Dry :1591 Medium_Dry :1985
## Median :0.72251 Medium_Sweet: 253 Medium_Sweet: 586
## Mean :0.85776 Sweet : 1 Sweet : 41
## 3rd Qu.:1.28738
## Max. :7.02616
Red Wine
## X fixed.acidity volatile.acidity citric.acid
## Min. : 1.0 Min. : 4.60 Min. :0.1200 Min. :0.000
## 1st Qu.: 400.5 1st Qu.: 7.10 1st Qu.:0.3900 1st Qu.:0.090
## Median : 800.0 Median : 7.90 Median :0.5200 Median :0.260
## Mean : 800.0 Mean : 8.32 Mean :0.5278 Mean :0.271
## 3rd Qu.:1199.5 3rd Qu.: 9.20 3rd Qu.:0.6400 3rd Qu.:0.420
## Max. :1599.0 Max. :15.90 Max. :1.5800 Max. :1.000
## residual.sugar chlorides free.sulfur.dioxide
## Min. : 0.900 Min. :0.01200 Min. : 1.00
## 1st Qu.: 1.900 1st Qu.:0.07000 1st Qu.: 7.00
## Median : 2.200 Median :0.07900 Median :14.00
## Mean : 2.539 Mean :0.08747 Mean :15.87
## 3rd Qu.: 2.600 3rd Qu.:0.09000 3rd Qu.:21.00
## Max. :15.500 Max. :0.61100 Max. :72.00
## total.sulfur.dioxide density pH sulphates
## Min. : 6.00 Min. :0.9901 Min. :2.740 Min. :0.3300
## 1st Qu.: 22.00 1st Qu.:0.9956 1st Qu.:3.210 1st Qu.:0.5500
## Median : 38.00 Median :0.9968 Median :3.310 Median :0.6200
## Mean : 46.47 Mean :0.9967 Mean :3.311 Mean :0.6581
## 3rd Qu.: 62.00 3rd Qu.:0.9978 3rd Qu.:3.400 3rd Qu.:0.7300
## Max. :289.00 Max. :1.0037 Max. :4.010 Max. :2.0000
## alcohol quality type combined.acidity
## Min. : 8.40 Min. :3.000 Red:1599 Min. : 5.270
## 1st Qu.: 9.50 1st Qu.:5.000 1st Qu.: 7.827
## Median :10.20 Median :6.000 Median : 8.720
## Mean :10.42 Mean :5.636 Mean : 9.118
## 3rd Qu.:11.10 3rd Qu.:6.000 3rd Qu.:10.070
## Max. :14.90 Max. :8.000 Max. :17.045
## s.a.ratio taste taste.due.to.pH
## Min. :0.1053 Dry :1580 Dry :717
## 1st Qu.:0.2117 Medium_Dry: 19 Medium_Dry :691
## Median :0.2482 Medium_Sweet:191
## Mean :0.2854
## 3rd Qu.:0.3008
## Max. :2.0807
## Warning in loop_apply(n, do.ply): position_stack requires constant width:
## output may be incorrect
## Warning in loop_apply(n, do.ply): position_stack requires constant width:
## output may be incorrect
## Warning in loop_apply(n, do.ply): position_stack requires constant width:
## output may be incorrect
## Warning in loop_apply(n, do.ply): position_stack requires constant width:
## output may be incorrect
## [1] 1
Free Sulphur Dioxide
sum(wqw$total.sulfur.dioxide >300)
## [1] 6
Total Sulphur Dioxide
Total Acidic Content
## [1] 132
Combined Acidity
Taste of White Wine
## Dry Medium_Dry Medium_Sweet Sweet
## 3053 1591 253 1
Taste of Red Wine
## Dry Medium_Dry
## 1580 19
Taste of White Wine due to PH
## Dry Medium_Dry Medium_Sweet Sweet
## 2286 1985 586 41
Taste of Red Wine due to PH
## Dry Medium_Dry Medium_Sweet
## 717 691 191
## X fixed.acidity volatile.acidity citric.acid residual.sugar
## 485 485 6.2 0.370 0.30 6.6
## 1218 1218 8.0 0.610 0.38 12.1
## 4916 18 8.1 0.560 0.28 1.7
## 4918 20 7.9 0.320 0.51 1.8
## 4941 43 7.5 0.490 0.20 2.6
## 4980 82 7.8 0.430 0.70 1.9
## 4982 84 7.3 0.670 0.26 1.8
## 5005 107 7.8 0.410 0.68 1.7
## 5050 152 9.2 0.520 1.00 3.4
## 5068 170 7.5 0.705 0.24 1.8
## 5125 227 8.9 0.590 0.50 2.0
## 5157 259 7.7 0.410 0.76 1.8
## 5180 282 7.7 0.270 0.68 3.5
## 5190 292 11.0 0.200 0.48 2.0
## 5350 452 8.4 0.370 0.53 1.8
## 5591 693 8.6 0.490 0.51 2.0
## 5629 731 9.5 0.550 0.66 2.3
## 5653 755 7.8 0.480 0.68 1.7
## 5950 1052 8.5 0.460 0.59 1.4
## 6064 1166 8.5 0.440 0.50 1.9
## 6159 1261 8.6 0.635 0.68 1.8
## 6218 1320 9.1 0.760 0.68 1.7
## 6269 1371 8.7 0.780 0.51 1.7
## 6271 1373 8.7 0.780 0.51 1.7
## chlorides free.sulfur.dioxide total.sulfur.dioxide density pH
## 485 0.346 79 200 0.99540 3.29
## 1218 0.301 24 220 0.99930 2.94
## 4916 0.368 16 56 0.99680 3.11
## 4918 0.341 17 56 0.99690 3.04
## 4941 0.332 8 14 0.99680 3.21
## 4980 0.464 22 67 0.99740 3.13
## 4982 0.401 16 51 0.99690 3.16
## 5005 0.467 18 69 0.99730 3.08
## 5050 0.610 32 69 0.99960 2.74
## 5068 0.360 15 63 0.99640 3.00
## 5125 0.337 27 81 0.99640 3.04
## 5157 0.611 8 45 0.99680 3.06
## 5180 0.358 5 10 0.99720 3.25
## 5190 0.343 6 18 0.99790 3.30
## 5350 0.413 9 26 0.99790 3.06
## 5591 0.422 16 62 0.99790 3.03
## 5629 0.387 12 37 0.99820 3.17
## 5653 0.415 14 32 0.99656 3.09
## 5950 0.414 16 45 0.99702 3.03
## 6064 0.369 15 38 0.99634 3.01
## 6159 0.403 19 56 0.99632 3.02
## 6218 0.414 18 64 0.99652 2.90
## 6269 0.415 12 66 0.99623 3.00
## 6271 0.415 12 66 0.99623 3.00
## sulphates alcohol quality type combined.acidity s.a.ratio taste
## 485 0.58 9.6 5 White 6.870 0.9606987 Dry
## 1218 0.48 9.2 5 White 8.990 1.3459399 Medium_Dry
## 4916 1.28 9.3 5 Red 8.940 0.1901566 Dry
## 4918 1.08 9.2 6 Red 8.730 0.2061856 Dry
## 4941 0.90 10.5 6 Red 8.190 0.3174603 Dry
## 4980 1.28 9.4 5 Red 8.930 0.2127660 Dry
## 4982 1.14 9.4 5 Red 8.230 0.2187120 Dry
## 5005 1.31 9.3 5 Red 8.890 0.1912261 Dry
## 5050 2.00 9.4 4 Red 10.720 0.3171642 Dry
## 5068 1.59 9.5 5 Red 8.445 0.2131439 Dry
## 5125 1.61 9.5 6 Red 9.990 0.2002002 Dry
## 5157 1.26 9.4 5 Red 8.870 0.2029312 Dry
## 5180 1.08 9.9 7 Red 8.650 0.4046243 Dry
## 5190 0.71 10.5 5 Red 11.680 0.1712329 Dry
## 5350 1.06 9.1 6 Red 9.300 0.1935484 Dry
## 5591 1.17 9.0 5 Red 9.600 0.2083333 Dry
## 5629 0.67 9.6 5 Red 10.710 0.2147526 Dry
## 5653 1.06 9.1 6 Red 8.960 0.1897321 Dry
## 5950 1.34 9.2 5 Red 9.550 0.1465969 Dry
## 6064 1.10 9.4 5 Red 9.440 0.2012712 Dry
## 6159 1.15 9.3 5 Red 9.915 0.1815431 Dry
## 6218 1.33 9.1 6 Red 10.540 0.1612903 Dry
## 6269 1.17 9.2 5 Red 9.990 0.1701702 Dry
## 6271 1.17 9.2 5 Red 9.990 0.1701702 Dry
## taste.due.to.pH
## 485 Dry
## 1218 Medium_Dry
## 4916 Dry
## 4918 Dry
## 4941 Dry
## 4980 Dry
## 4982 Dry
## 5005 Dry
## 5050 Dry
## 5068 Dry
## 5125 Dry
## 5157 Dry
## 5180 Dry
## 5190 Medium_Dry
## 5350 Dry
## 5591 Dry
## 5629 Dry
## 5653 Dry
## 5950 Dry
## 6064 Dry
## 6159 Dry
## 6218 Dry
## 6269 Dry
## 6271 Dry
White Wine
##
## Pearson's product-moment correlation
##
## data: wqw$alcohol and wqw$quality
## t = 33.8585, df = 4896, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.4126015 0.4579941
## sample estimates:
## cor
## 0.4355747
Red Wine
##
## Pearson's product-moment correlation
##
## data: wqr$alcohol and wqr$quality
## t = 21.6395, df = 1597, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.4373540 0.5132081
## sample estimates:
## cor
## 0.4761663
Correlation table of White Wine
## Fixed Acid Volatile Acid Citric Acid Sugar Salt Free SO2
## Fixed Acid 1.00 -0.02 0.29 0.09 0.02 -0.05
## Volatile Acid -0.02 1.00 -0.15 0.06 0.07 -0.10
## Citric Acid 0.29 -0.15 1.00 0.09 0.11 0.09
## Sugar 0.09 0.06 0.09 1.00 0.09 0.30
## Salt 0.02 0.07 0.11 0.09 1.00 0.10
## Free SO2 -0.05 -0.10 0.09 0.30 0.10 1.00
## Total SO2 0.09 0.09 0.12 0.40 0.20 0.62
## Density 0.27 0.03 0.15 0.84 0.26 0.29
## pH -0.43 -0.03 -0.16 -0.19 -0.09 0.00
## SO4 -0.02 -0.04 0.06 -0.03 0.02 0.06
## Alcohol -0.12 0.07 -0.08 -0.45 -0.36 -0.25
## Quality -0.11 -0.19 -0.01 -0.10 -0.21 0.01
## Total SO2 Density pH SO4 Alcohol Quality
## Fixed Acid 0.09 0.27 -0.43 -0.02 -0.12 -0.11
## Volatile Acid 0.09 0.03 -0.03 -0.04 0.07 -0.19
## Citric Acid 0.12 0.15 -0.16 0.06 -0.08 -0.01
## Sugar 0.40 0.84 -0.19 -0.03 -0.45 -0.10
## Salt 0.20 0.26 -0.09 0.02 -0.36 -0.21
## Free SO2 0.62 0.29 0.00 0.06 -0.25 0.01
## Total SO2 1.00 0.53 0.00 0.13 -0.45 -0.17
## Density 0.53 1.00 -0.09 0.07 -0.78 -0.31
## pH 0.00 -0.09 1.00 0.16 0.12 0.10
## SO4 0.13 0.07 0.16 1.00 -0.02 0.05
## Alcohol -0.45 -0.78 0.12 -0.02 1.00 0.44
## Quality -0.17 -0.31 0.10 0.05 0.44 1.00
Correlation plot of White Wine
## Warning in loop_apply(n, do.ply): Stacking not well defined when ymin != 0
## Warning in loop_apply(n, do.ply): Stacking not well defined when ymin != 0
## Warning in loop_apply(n, do.ply): Stacking not well defined when ymin != 0
## Warning in loop_apply(n, do.ply): position_stack requires constant width:
## output may be incorrect
Correlation table of Red Wine
## Fixed Acid Volatile Acid Citric Acid Sugar Salt Free SO2
## Fixed Acid 1.00 -0.26 0.67 0.11 0.09 -0.15
## Volatile Acid -0.26 1.00 -0.55 0.00 0.06 -0.01
## Citric Acid 0.67 -0.55 1.00 0.14 0.20 -0.06
## Sugar 0.11 0.00 0.14 1.00 0.06 0.19
## Salt 0.09 0.06 0.20 0.06 1.00 0.01
## Free SO2 -0.15 -0.01 -0.06 0.19 0.01 1.00
## Total SO2 -0.11 0.08 0.04 0.20 0.05 0.67
## Density 0.67 0.02 0.36 0.36 0.20 -0.02
## pH -0.68 0.23 -0.54 -0.09 -0.27 0.07
## SO4 0.18 -0.26 0.31 0.01 0.37 0.05
## Alcohol -0.06 -0.20 0.11 0.04 -0.22 -0.07
## Quality 0.12 -0.39 0.23 0.01 -0.13 -0.05
## Total SO2 Density pH SO4 Alcohol Quality
## Fixed Acid -0.11 0.67 -0.68 0.18 -0.06 0.12
## Volatile Acid 0.08 0.02 0.23 -0.26 -0.20 -0.39
## Citric Acid 0.04 0.36 -0.54 0.31 0.11 0.23
## Sugar 0.20 0.36 -0.09 0.01 0.04 0.01
## Salt 0.05 0.20 -0.27 0.37 -0.22 -0.13
## Free SO2 0.67 -0.02 0.07 0.05 -0.07 -0.05
## Total SO2 1.00 0.07 -0.07 0.04 -0.21 -0.19
## Density 0.07 1.00 -0.34 0.15 -0.50 -0.17
## pH -0.07 -0.34 1.00 -0.20 0.21 -0.06
## SO4 0.04 0.15 -0.20 1.00 0.09 0.25
## Alcohol -0.21 -0.50 0.21 0.09 1.00 0.48
## Quality -0.19 -0.17 -0.06 0.25 0.48 1.00
Correlation plot of Red Wine
## Warning in loop_apply(n, do.ply): Stacking not well defined when ymin != 0
## Warning in loop_apply(n, do.ply): Stacking not well defined when ymin != 0
## Warning in loop_apply(n, do.ply): position_stack requires constant width:
## output may be incorrect
Revisiting Alcohol distribution for both types of wines
Scatter Plot for White wine (Quality vs. Alcohol)
Table for Quality vs. Alcohol of White wine
## wqw$quality: 3
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.00 9.55 10.45 10.34 11.00 12.60
## --------------------------------------------------------
## wqw$quality: 4
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.40 10.10 10.15 10.75 13.50
## --------------------------------------------------------
## wqw$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.000 9.200 9.500 9.809 10.300 13.600
## --------------------------------------------------------
## wqw$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.50 9.60 10.50 10.58 11.40 14.00
## --------------------------------------------------------
## wqw$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.60 10.60 11.40 11.37 12.30 14.20
## --------------------------------------------------------
## wqw$quality: 8
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.50 11.00 12.00 11.64 12.60 14.00
## --------------------------------------------------------
## wqw$quality: 9
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 10.40 12.40 12.50 12.18 12.70 12.90
Box Plot for White wine (Quality vs. Alcohol)
Scatter Plot for Red wine (Quality vs. Alcohol)
Table for Quality vs. Alcohol of Red wine
## wqr$quality: 3
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.400 9.725 9.925 9.955 10.580 11.000
## --------------------------------------------------------
## wqr$quality: 4
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 9.00 9.60 10.00 10.27 11.00 13.10
## --------------------------------------------------------
## wqr$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.5 9.4 9.7 9.9 10.2 14.9
## --------------------------------------------------------
## wqr$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.80 10.50 10.63 11.30 14.00
## --------------------------------------------------------
## wqr$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 9.20 10.80 11.50 11.47 12.10 14.00
## --------------------------------------------------------
## wqr$quality: 8
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 9.80 11.32 12.15 12.09 12.88 14.00
Box Plot for Red wine (Quality vs. Alcohol)
Plot for Quality vs. Taste of White wine
Table for Quality vs. Taste of White wine
## wqw$taste: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.958 7.000 9.000
## --------------------------------------------------------
## wqw$taste: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.775 6.000 9.000
## --------------------------------------------------------
## wqw$taste: Medium_Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4.000 5.000 6.000 5.553 6.000 8.000
## --------------------------------------------------------
## wqw$taste: Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 6 6 6 6 6 6
Table for Quality vs. Taste (pH) of White wine
## wqw$taste.due.to.pH: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.886 6.000 9.000
## --------------------------------------------------------
## wqw$taste.due.to.pH: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.907 6.000 9.000
## --------------------------------------------------------
## wqw$taste.due.to.pH: Medium_Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.787 6.000 8.000
## --------------------------------------------------------
## wqw$taste.due.to.pH: Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 5.000 5.000 5.000 5.341 6.000 6.000
Plot for Quality vs. Taste of Red wine
Table for Quality vs. Taste of Red wine
## wqr$taste: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.637 6.000 8.000
## --------------------------------------------------------
## wqr$taste: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4.000 5.000 6.000 5.526 6.000 6.000
Table for Quality vs. Taste (pH) of Red wine
## wqr$taste.due.to.pH: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.681 6.000 8.000
## --------------------------------------------------------
## wqr$taste.due.to.pH: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.618 6.000 8.000
## --------------------------------------------------------
## wqr$taste.due.to.pH: Medium_Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.000 5.000 6.000 5.534 6.000 8.000
Distribution of pH for wine samples revisted
Scatter Plot for White wine (Alcohol vs. pH)
Correlation coefficient for White wine (Alcohol vs. pH)
##
## Pearson's product-moment correlation
##
## data: wqw$alcohol and wqw$pH
## t = 8.5601, df = 4896, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.09374446 0.14893205
## sample estimates:
## cor
## 0.1214321
Scatter Plot for Red wine (Alcohol vs. pH)
Correlation coefficient for Red wine (Alcohol vs. pH)
##
## Pearson's product-moment correlation
##
## data: wqr$alcohol and wqr$pH
## t = 8.397, df = 1597, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.1582061 0.2521123
## sample estimates:
## cor
## 0.2056325
Frequency Plot for Alcohol vs. Taste of White wine
Box Plot for Alcohol vs. Taste of White wine
Table for Alcohol vs. Taste of White wine
## wqw$taste: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.00 10.00 10.90 10.94 11.80 14.20
## --------------------------------------------------------
## wqw$taste: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.000 9.100 9.500 9.871 10.400 14.050
## --------------------------------------------------------
## wqw$taste: Medium_Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.500 8.800 9.100 9.407 9.600 13.000
## --------------------------------------------------------
## wqw$taste: Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 11.7 11.7 11.7 11.7 11.7 11.7
Table for Alcohol vs. Taste (pH) of White wine
## wqw$taste.due.to.pH: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.90 10.80 10.89 11.89 14.20
## --------------------------------------------------------
## wqw$taste.due.to.pH: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.00 9.30 10.00 10.26 11.00 14.05
## --------------------------------------------------------
## wqw$taste.due.to.pH: Medium_Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.000 9.100 9.800 9.981 10.500 14.000
## --------------------------------------------------------
## wqw$taste.due.to.pH: Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.700 8.800 9.500 9.622 10.100 12.400
Frequency Plot for Alcohol vs. Taste of Red wine
Box Plot for Alcohol vs. Taste of Red wine
Table for Alcohol vs. Taste of Red wine
## wqr$taste: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.50 10.20 10.43 11.10 14.90
## --------------------------------------------------------
## wqr$taste: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.800 9.200 9.900 9.984 10.400 12.200
Table for Alcohol vs. Taste (pH) of Red wine
## wqr$taste.due.to.pH: Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.50 10.00 10.29 11.00 14.90
## --------------------------------------------------------
## wqr$taste.due.to.pH: Medium_Dry
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.70 9.50 10.30 10.41 11.00 14.00
## --------------------------------------------------------
## wqr$taste.due.to.pH: Medium_Sweet
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 9.233 9.850 10.800 10.960 11.700 14.000
Sulphates revisited
Scatter Plot for White wine (Quality vs. Sulphates)
Box Plot for White wine (Quality vs. Sulphates)
Table and Correlation Coefficient for Quality vs. Sulphates of White wine
## wqw$quality: 3
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2800 0.3800 0.4400 0.4745 0.5425 0.7400
## --------------------------------------------------------
## wqw$quality: 4
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2500 0.3800 0.4700 0.4761 0.5400 0.8700
## --------------------------------------------------------
## wqw$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2700 0.4200 0.4700 0.4822 0.5300 0.8800
## --------------------------------------------------------
## wqw$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2300 0.4100 0.4800 0.4911 0.5500 1.0600
## --------------------------------------------------------
## wqw$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2200 0.4100 0.4800 0.5031 0.5800 1.0800
## --------------------------------------------------------
## wqw$quality: 8
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2500 0.3800 0.4600 0.4862 0.5850 0.9500
## --------------------------------------------------------
## wqw$quality: 9
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.360 0.420 0.460 0.466 0.480 0.610
##
## Pearson's product-moment correlation
##
## data: wqw$sulphates and wqw$quality
## t = 3.7613, df = 4896, p-value = 0.000171
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.02571007 0.08156172
## sample estimates:
## cor
## 0.05367788
Scatter Plot for Red wine (Quality vs. Sulphates)
Box Plot for Red wine (Quality vs. Sulphates)
Table and Correlation Coefficient for Quality vs. Sulphates of Red wine
## wqr$quality: 3
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.4000 0.5125 0.5450 0.5700 0.6150 0.8600
## --------------------------------------------------------
## wqr$quality: 4
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.3300 0.4900 0.5600 0.5964 0.6000 2.0000
## --------------------------------------------------------
## wqr$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.370 0.530 0.580 0.621 0.660 1.980
## --------------------------------------------------------
## wqr$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.4000 0.5800 0.6400 0.6753 0.7500 1.9500
## --------------------------------------------------------
## wqr$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.3900 0.6500 0.7400 0.7413 0.8300 1.3600
## --------------------------------------------------------
## wqr$quality: 8
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.6300 0.6900 0.7400 0.7678 0.8200 1.1000
##
## Pearson's product-moment correlation
##
## data: wqr$sulphates and wqr$quality
## t = 10.3798, df = 1597, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.2049011 0.2967610
## sample estimates:
## cor
## 0.2513971
Scatter Plot for White wine (Quality vs. pH)
Box Plot for White wine (Quality vs. pH)
Table and Correlation Coefficient for Quality vs. pH of White wine
## wqw$quality: 3
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.870 3.035 3.215 3.188 3.325 3.550
## --------------------------------------------------------
## wqw$quality: 4
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.830 3.070 3.160 3.183 3.280 3.720
## --------------------------------------------------------
## wqw$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.790 3.080 3.160 3.169 3.240 3.790
## --------------------------------------------------------
## wqw$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.720 3.080 3.180 3.189 3.280 3.810
## --------------------------------------------------------
## wqw$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.840 3.100 3.200 3.214 3.320 3.820
## --------------------------------------------------------
## wqw$quality: 8
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.940 3.120 3.230 3.219 3.330 3.590
## --------------------------------------------------------
## wqw$quality: 9
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.200 3.280 3.280 3.308 3.370 3.410
##
## Pearson's product-moment correlation
##
## data: wqw$pH and wqw$quality
## t = 6.9917, df = 4896, p-value = 3.081e-12
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.07162022 0.12707983
## sample estimates:
## cor
## 0.09942725
Citric Acid Histogram for Red wine samples
Scatter Plot for Red wine (Quality vs. Citric Acid)
Box Plot for Red wine (Quality vs. Citric Acid)
Table and Correlation Coefficient for Quality vs. Citric Acid of Red wine
## wqr$quality: 3
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0050 0.0350 0.1710 0.3275 0.6600
## --------------------------------------------------------
## wqr$quality: 4
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0300 0.0900 0.1742 0.2700 1.0000
## --------------------------------------------------------
## wqr$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0900 0.2300 0.2437 0.3600 0.7900
## --------------------------------------------------------
## wqr$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.0900 0.2600 0.2738 0.4300 0.7800
## --------------------------------------------------------
## wqr$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0000 0.3050 0.4000 0.3752 0.4900 0.7600
## --------------------------------------------------------
## wqr$quality: 8
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0300 0.3025 0.4200 0.3911 0.5300 0.7200
##
## Pearson's product-moment correlation
##
## data: wqr$citric.acid and wqr$quality
## t = 9.2875, df = 1597, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.1793415 0.2723711
## sample estimates:
## cor
## 0.2263725
Scatter Plot for White wine (Density vs. Residual Sugar)
## Warning in loop_apply(n, do.ply): Removed 3 rows containing missing values
## (stat_smooth).
## Warning in loop_apply(n, do.ply): Removed 3 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 13 rows containing missing
## values (geom_path).
Correlation coefficient for White wine (Density vs. Residual Sugar)
##
## Pearson's product-moment correlation
##
## data: wqw$density and wqw$residual.sugar
## t = 107.8749, df = 4896, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.8304732 0.8470698
## sample estimates:
## cor
## 0.8389665
Scatter Plot for Red wine (Density vs. Fixed Acidity)
Correlation coefficient for Red wine (Density vs. Fixed Acidity)
##
## Pearson's product-moment correlation
##
## data: wqr$density and wqr$fixed.acidity
## t = 35.8771, df = 1597, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.6399847 0.6943302
## sample estimates:
## cor
## 0.6680473
Density Plot of Alcohol with Quality for White wine
Density Plot of Alcohol with Quality for Red wine
Box Plot for White wine (Quality vs. Alcohol) with Taste
Box Plot for White wine (Quality vs. Alcohol) with Taste due to pH
Box Plot for Red wine (Quality vs. Alcohol) with Taste
Box Plot for Red wine (Quality vs. Alcohol) with Taste due to pH
Density Plot of pH with Quality for White wine
Density Plot of pH with Quality for Red wine
Scatter Plot for White wine (Alcohol vs. pH) with Quality
Scatter Plot for Red wine (Alcohol vs. pH) with Quality
Density Plot of Sulphates with Quality for White wine
Density Plot of Sulphates with Quality for Red wine
Scatter Plot for White wine (Sulphates vs. Alcohol) with Quality
Scatter Plot for White wine (Sulphates vs. Alcohol) with Quality [zoomed]
## Warning in loop_apply(n, do.ply): Removed 700 rows containing missing
## values (geom_point).
Scatter Plot for Red wine (Sulphates vs. Alcohol) with Quality
## Warning in loop_apply(n, do.ply): Removed 8 rows containing missing values
## (geom_point).
Density Plot of Residual Sugar with Quality for White wine
Density Plot of Residual Sugar with Quality for Red wine
Scatter Plot for White wine (Residual Sugar vs. Alcohol) with Quality
## Warning in loop_apply(n, do.ply): Removed 5 rows containing missing values
## (geom_point).
Scatter Plot for Red wine (Residual Sugar vs. Alcohol) with Quality [zoomed]
## Warning in loop_apply(n, do.ply): Removed 129 rows containing missing
## values (geom_point).
Total Acidic Content with Quality (White wine on left and Red wine on right)
Scatter plot for Total Acidic Content and Alcohol with Quality (White wine on left and Red wine on right)
## Warning in loop_apply(n, do.ply): Removed 4 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 9 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 19 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 8 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 31 rows containing missing
## values (geom_point).
Density Plot of Chlorides with Quality for White wine
Density Plot of Chlorides with Quality for Red wine
Scatter Plot for (Chlorides vs. Alcohol) with Quality [Facet Wrap]
## Warning in loop_apply(n, do.ply): Removed 1 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 9 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 3 rows containing missing values
## (geom_point).
SO2 with Quality (White wine on left and Red wine on right)
Scatter plot for Total Sulphur Dioxide and Alcohol with Qualtiy (White wine on left and Red wine on right)
## Warning in loop_apply(n, do.ply): Removed 6 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 9 rows containing missing values
## (geom_point).
## Warning in loop_apply(n, do.ply): Removed 10 rows containing missing
## values (geom_point).
## Warning in loop_apply(n, do.ply): Removed 8 rows containing missing values
## (geom_point).
Density Plot of Density with Quality for White wine
Density Plot of Density with Quality for Red wine
Scatter Plot for (Density vs. Alcohol) with Quality [Facet Wrap]
## Warning in loop_apply(n, do.ply): Removed 3 rows containing missing values
## (geom_point).
Scatter Plot for (Density vs. Residual Sugar) with Quality
## Warning in loop_apply(n, do.ply): Removed 5 rows containing missing values
## (geom_point).
Scatter Plot for (Density vs. Fixed Acidity) with Quality
##
## Calls:
## m1: lm(formula = quality ~ alcohol, data = combined_wq)
## m2: lm(formula = quality ~ alcohol + pH, data = combined_wq)
## m3: lm(formula = quality ~ alcohol + pH + sulphates, data = combined_wq)
## m4: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5),
## data = combined_wq)
## m5: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide, data = combined_wq)
## m6: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)), data = combined_wq)
## m7: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity,
## data = combined_wq)
## m8: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid, data = combined_wq)
## m9: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid + I(log10(density)), data = combined_wq)
## m10: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid + I(log10(density)) + I(log10(total.sulfur.dioxide)),
## data = combined_wq)
## m11: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid + I(log10(density)) + I(log10(total.sulfur.dioxide)) +
## residual.sugar, data = combined_wq)
## m12: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid + I(log10(density)) + I(log10(total.sulfur.dioxide)) +
## residual.sugar + I(log10(combined.acidity)), data = combined_wq)
## m13: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid + I(log10(density)) + I(log10(total.sulfur.dioxide)) +
## residual.sugar + I(log10(combined.acidity)) + s.a.ratio,
## data = combined_wq)
## m14: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid + I(log10(density)) + I(log10(total.sulfur.dioxide)) +
## residual.sugar + I(log10(combined.acidity)) + s.a.ratio +
## taste, data = combined_wq)
## m15: lm(formula = quality ~ alcohol + pH + sulphates + I(sulphates^5) +
## free.sulfur.dioxide + I(free.sulfur.dioxide^(1/10)) + volatile.acidity +
## citric.acid + I(log10(density)) + I(log10(total.sulfur.dioxide)) +
## residual.sugar + I(log10(combined.acidity)) + s.a.ratio +
## taste + fixed.acidity, data = combined_wq)
##
## ===================================================================================================================================================================================================================
## m1 m2 m3 m4 m5 m6 m7 m8 m9 m10 m11 m12 m13 m14 m15
## -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
## (Intercept) 2.405*** 2.982*** 2.987*** 3.023*** 2.277*** -1.983*** -1.028** -0.927* -1.316** -2.164*** -2.466*** -4.232*** -4.160*** -4.748*** -3.973***
## (0.086) (0.204) (0.204) (0.204) (0.209) (0.396) (0.388) (0.401) (0.404) (0.407) (0.406) (0.574) (0.594) (0.605) (0.747)
## alcohol 0.325*** 0.328*** 0.329*** 0.329*** 0.348*** 0.342*** 0.323*** 0.323*** 0.381*** 0.352*** 0.303*** 0.261*** 0.261*** 0.246*** 0.238***
## (0.008) (0.008) (0.008) (0.008) (0.008) (0.008) (0.008) (0.008) (0.011) (0.012) (0.013) (0.016) (0.016) (0.017) (0.018)
## pH -0.189** -0.241*** -0.267*** -0.195** -0.187** 0.073 0.055 0.024 -0.044 0.101 0.360*** 0.359*** 0.402*** 0.417***
## (0.061) (0.062) (0.063) (0.062) (0.061) (0.061) (0.064) (0.063) (0.063) (0.065) (0.088) (0.088) (0.090) (0.090)
## sulphates 0.284*** 0.385*** 0.551*** 0.681*** 0.821*** 0.834*** 0.693*** 0.547*** 0.767*** 0.829*** 0.828*** 0.844*** 0.850***
## (0.066) (0.076) (0.076) (0.076) (0.074) (0.075) (0.077) (0.078) (0.082) (0.083) (0.083) (0.083) (0.083)
## I(sulphates^5) -0.038** -0.043** -0.052*** -0.050*** -0.051*** -0.043** -0.034** -0.040** -0.039** -0.039** -0.039** -0.038**
## (0.014) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013) (0.013)
## free.sulfur.dioxide 0.007*** -0.009*** -0.009*** -0.008*** -0.009*** -0.013*** -0.014*** -0.014*** -0.014*** -0.015*** -0.015***
## (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001)
## I(free.sulfur.dioxide^(1/10)) 3.433*** 2.517*** 2.499*** 2.685*** 4.660*** 4.717*** 4.700*** 4.705*** 4.799*** 4.821***
## (0.272) (0.268) (0.269) (0.269) (0.319) (0.317) (0.317) (0.317) (0.316) (0.316)
## volatile.acidity -1.247*** -1.269*** -1.429*** -1.558*** -1.380*** -1.396*** -1.399*** -1.397*** -1.300***
## (0.063) (0.067) (0.071) (0.071) (0.074) (0.074) (0.074) (0.074) (0.092)
## citric.acid -0.070 -0.206** -0.131 0.013 -0.116 -0.118 -0.112 -0.045
## (0.072) (0.075) (0.074) (0.076) (0.081) (0.081) (0.081) (0.090)
## I(log10(density)) 78.845*** 60.937*** -44.217* -132.737*** -132.288*** -151.958*** -163.429***
## (11.236) (11.239) (17.213) (26.631) (26.649) (28.208) (28.938)
## I(log10(total.sulfur.dioxide)) -0.598*** -0.758*** -0.763*** -0.767*** -0.798*** -0.799***
## (0.053) (0.056) (0.056) (0.057) (0.057) (0.057)
## residual.sugar 0.028*** 0.043*** 0.050** 0.024 0.033
## (0.004) (0.005) (0.016) (0.017) (0.018)
## I(log10(combined.acidity)) 1.267*** 1.196*** 1.600*** -0.092
## (0.291) (0.326) (0.348) (1.017)
## s.a.ratio -0.057 0.322* 0.262
## (0.118) (0.132) (0.136)
## taste: .L 0.179 0.183
## (0.559) (0.559)
## taste: .Q 0.550 0.555
## (0.408) (0.407)
## taste: .C 0.365 0.367*
## (0.187) (0.187)
## fixed.acidity 0.089
## (0.050)
## -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
## R-squared 0.197 0.199 0.201 0.202 0.223 0.242 0.284 0.285 0.290 0.304 0.311 0.313 0.313 0.318 0.318
## adj. R-squared 0.197 0.198 0.200 0.201 0.222 0.241 0.284 0.284 0.289 0.303 0.309 0.311 0.311 0.316 0.316
## sigma 0.782 0.782 0.781 0.780 0.770 0.761 0.739 0.739 0.736 0.729 0.726 0.725 0.725 0.722 0.722
## F 1597.641 804.749 544.025 410.377 372.584 344.582 368.568 322.613 294.371 282.976 265.644 245.759 226.845 188.468 177.624
## p 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000
## Log-likelihood -7623.404 -7618.549 -7609.411 -7605.540 -7518.180 -7439.467 -7250.383 -7249.909 -7225.344 -7161.667 -7129.474 -7120.000 -7119.884 -7096.585 -7095.014
## Deviance 3975.734 3969.796 3958.645 3953.930 3849.017 3756.874 3544.442 3543.924 3517.226 3448.953 3414.943 3404.997 3404.876 3380.543 3378.909
## AIC 15252.809 15245.098 15228.821 15223.079 15050.360 14894.933 14518.766 14519.817 14472.687 14347.334 14284.948 14267.999 14269.768 14229.170 14228.028
## BIC 15273.146 15272.214 15262.717 15263.754 15097.814 14949.166 14579.778 14587.608 14547.257 14428.683 14373.076 14362.907 14371.454 14351.194 14356.831
## N 6497 6497 6497 6497 6497 6497 6497 6497 6497 6497 6497 6497 6497 6497 6497
## ===================================================================================================================================================================================================================
## sub_q_wqw$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.790 3.080 3.160 3.169 3.240 3.790
## --------------------------------------------------------
## sub_q_wqw$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.720 3.080 3.180 3.189 3.280 3.810
## --------------------------------------------------------
## sub_q_wqw$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.840 3.100 3.200 3.214 3.320 3.820
## sub_q_wqw$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2700 0.4200 0.4700 0.4822 0.5300 0.8800
## --------------------------------------------------------
## sub_q_wqw$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2300 0.4100 0.4800 0.4911 0.5500 1.0600
## --------------------------------------------------------
## sub_q_wqw$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.2200 0.4100 0.4800 0.5031 0.5800 1.0800
## sub_q_wqw$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.000 9.200 9.500 9.809 10.300 13.600
## --------------------------------------------------------
## sub_q_wqw$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.50 9.60 10.50 10.58 11.40 14.00
## --------------------------------------------------------
## sub_q_wqw$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.60 10.60 11.40 11.37 12.30 14.20
## pH sulphates alcohol quality
## pH 1.00 0.15 0.12 0.10
## sulphates 0.15 1.00 -0.02 0.06
## alcohol 0.12 -0.02 1.00 0.45
## quality 0.10 0.06 0.45 1.00
## sub_q_wqr$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.880 3.200 3.300 3.305 3.400 3.740
## --------------------------------------------------------
## sub_q_wqr$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.860 3.220 3.320 3.318 3.410 4.010
## --------------------------------------------------------
## sub_q_wqr$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 2.920 3.200 3.280 3.291 3.380 3.780
## sub_q_wqr$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.370 0.530 0.580 0.621 0.660 1.980
## --------------------------------------------------------
## sub_q_wqr$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.4000 0.5800 0.6400 0.6753 0.7500 1.9500
## --------------------------------------------------------
## sub_q_wqr$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.3900 0.6500 0.7400 0.7413 0.8300 1.3600
## sub_q_wqr$quality: 5
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.5 9.4 9.7 9.9 10.2 14.9
## --------------------------------------------------------
## sub_q_wqr$quality: 6
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 8.40 9.80 10.50 10.63 11.30 14.00
## --------------------------------------------------------
## sub_q_wqr$quality: 7
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 9.20 10.80 11.50 11.47 12.10 14.00
## pH sulphates alcohol quality
## pH 1.00 -0.18 0.2 -0.01
## sulphates -0.18 1.00 0.1 0.24
## alcohol 0.20 0.10 1.0 0.50
## quality -0.01 0.24 0.5 1.00
Comparison of r^2 for subsets for White wine
Comparison of r^2 for subsets for Red wine